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modeling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
finding » findings (Expand Search)
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181
Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022“…An efficient optimization method is needed to address complicated problems and find optimal solutions. The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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182
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
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Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development
Published 2025“…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. …”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…The forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization algorithm. …”
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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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192
Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
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193
SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
Published 2018“…This paper describes SemIndex+, a semantic-aware indexing and querying framework that allows semantic search, result selection, and result ranking of structured (relational DB-style), unstructured (IR-style), and partly structured (NoSQL) data. Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …”
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194
GIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing
Published 2024“…The motivation for this research stems from the increasing demand for efficient resource utilization and task management in cloud computing, driven by the proliferation of Internet of Things (IoT) devices and the growing reliance on cloud‐based services. Traditional task scheduling algorithms often face challenges in handling dynamic workloads, heterogeneous resources, and varying performance objectives, necessitating innovative optimization techniques. …”
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195
Practical single node failure recovery using fractional repetition codes in data centers
Published 2016“…Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…In order to mitigate the charging effects of electric vehicles on the hybrid AC–DC microgrid operation, some remotely switches are considered in the system which make it possible for changing the topology and power flow way. In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …”
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198
A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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199
Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
Published 2021“…Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”
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KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”